Adaptive control strategy for velocity control of a linear switched reluctance motor

Abstract

A new adaptive control strategy for a double-sided linear switched reluctance motor is proposed in this work. Switched reluctance motors inherently have non-linear dynamics that complicates their analysis and control. The Takagi–Sugeno fuzzy logic system has been used in this work to achieve an appropriate adaptive control system for the proposed linear motor. The fuzzy system has been heightened by non-linear rule consequences and a time-varying parameter. Updated laws have been designed to refresh the amount of the parameter consequently the suggested control system shows a stable performance in control of switched reluctance motors. The proposed control strategy is independent of the uncertainties of the motor dynamics and has an acceptable adaptability. This control method along with a conventional fuzzy logic based system have been studied on the proposed linear switched reluctance motor and their performances were compared in different performance conditions. An appropriate evaluation method has been used to compare the obtained results. The efficiency of the proposed method in different velocity commands has been examined and confirmed using appropriate simulation and experimental results.